Retrieval of nearshore bathymetry from Landsat 8 images: a tool for coastal monitoring in shallow waters

Nearshore bathymetry is likely to be the coastal variable that most limits the investigation of coastal processes and the accuracy of numerical models in coastal areas, as acquiring medium spatial resolution data in the nearshore is highly demanding and costly. As such, the ability to derive bathymetry using remote sensing techniques is a topic of increasing interest in coastalmonitoring and research. This contribution focuses on the application of the linear transform algorithm to obtain satellite-derived bathymetry (SDB) maps of the nearshore, at medium resolution (30 m), from freely available and easily accessible Landsat 8 imagery. The algorithm was tuned with available bathymetric Light Detection and Ranging (LiDAR) data for a 60-km-long nearshore stretch of a highly complex coastal system that includes barrier islands, exposed sandy beaches, and tidal inlets (Ria Formosa, Portugal). A comparison of the retrieved depths is presented, enabling the configuration of nearshore profiles and extracted isobaths to be explored and compared with traditional topographic/bathymetric techniques (e.g., high- and medium-resolution LiDAR data and survey-grade echo-sounding combined with high-precision positioning systems). The results demonstrate that the linear algorithm is efficient for retrieving bathymetry frommulti-spectral satellite data for shallowwater depths (0 to 12 m), showing amean bias of−0.2m, a median difference of −0.1 m, and a root mean square error of 0.89 m. Accuracy is shown to be depth dependent, an inherent limitation of passive optical detection systems. Accuracy further decreases in areas where turbidity is likely to be higher, such as locations adjacent to tidal inlets. The SDB maps provide reliable estimations of the shoreline position and of nearshore isobaths for different cases along the complex coastline analysed. The use of freely available satellite imagery proved to be a quick and reliable method for acquiring updated mediumresolution, high-frequency (days and weeks), low-cost bathymetric information for large areas and depths of up to 12 m in clear waters without wave breaking, allowing almost constant monitoring of the submerged beach and the shoreface.info:eu-repo/semantics/publishedVersio

Development of Geospatial and Temporal Characteristics for Hispaniola’s Lake Azuei and Enriquillo Using Landsat Imagery

In this paper, we used Landsat imagery for water body identification to create a novel 36-year surface area extent time series for lakes Azuei (Haiti) and Enriquillo (Dominican Republic) aimed at illuminating the dramatic temporal changes of these two lakes not just at yearly but at monthly or even sub-monthly scales. We used the Normalized Difference Water Index (NDWI) to extract water features and we also used spatial differentiation and thresholding techniques to remove clouds and associated shadows from the scene that were then passed through gap filling algorithms to complete and extract the lake extent polygons. We also explored the challenges that arrive from trying to combine RS-based Digital Elevation Model data with locally collected bathymetric data to yield a seamless representation of the topographic features of the rift valley that contains the two lakes. This “bathtub” model was then meshed with the lake extent polygons to compute lake volumes, maximum depths, and geospatially referenced lake levels rating curves. We used this data to examine the lakes and their geospatial characteristics in the context of the lakes’ growth/shrinking patterns. While we did not carry out a full hydrologic analysis we attempted to illuminate how specific lake levels cause what type of flooding and especially answered the questions if (a) Lake Azuei would ever spill into Lake Enriquillo, and (b) what the maximum lake levels need to be before spilling into neighboring watersheds

Tracking Multidecadal Lake Water Dynamics with Landsat Imagery and Topography/Bathymetry

An edited version of this paper was published by AGU. Copyright 2019 American Geophysical Union.Water resource management is of critical importance due to its close relationship with nearly every industry, field, and lifeform on this planet. The success of future water management will rely upon having detailed data of current and historic water dynamics. This research leverages Google Earth Engine and uses Landsat 5 imagery in conjunction with bathymetry and Shuttle Radar Topography Mission digital elevation model data to analyze long‐term lake dynamics (water surface elevation, surface area, volume, volume change, and frequency) for Lake McConaughy in Nebraska, USA. Water surface elevation was estimated by extracting elevation values from underlying bathymetry and digital elevations models using 5,994 different combinations of water indices, water boundaries, and statistics for 100 time periods spanning 1985–2009. Surface elevation calculations were as accurate as 0.768 m root mean square error (CI95% [0.657, 0.885]). Water volume change calculations found a maximum change of 1.568 km3 and a minimum total volume of only 23.97% of the maximum reservoir volume. Seasonal and long‐term trends were identified, which have major affects regarding regional agriculture, local recreation, and lake water quality. This research fills an existing gap in optical remote sensing‐based monitoring of lakes and reservoirs, is more robust and outperforms other commonly used monitoring techniques, increases the number of water bodies available for long‐term studies, introduces a scalable framework deployable within Google Earth Engine, and enables data collection of both gauged and ungauged water bodies, which will substantially increase our knowledge and understanding of these critical ecosystems

Coastal tidal effects on industrial thermal plumes in satellite imagery

Coastal tidal effects on thermal plumes are investigated exploiting remote sensing of two major coastal industrial installations. The installations use sea water as a coolant, which is then released back into coastal environments at a higher-than-ambient temperature, allowing the plume to be delineated from the ambient waters. Satellite-based thermal sensors observing the Earth at a spatial resolution of 90 and 100 m are used. It is possible to identify coastal features and thermal spatial distributions. This paper presents coastal tidal effects on detected plumes for two case studies: an intertidal embayment and open water exposure, both on the coast of the UK. We correlated the behaviours of thermal plumes using remotely sensed high resolution thermal imagery with tidal phases derived from tide gauges. The results show very distinct behaviours for the flood and ebb tides. The detected surface plume location was dependent on flow switching direction for the different types of tide. The detected surface area was dependent on the strength of the currents, with the largest area observed during the strongest currents. Understanding the dispersion of the plume is essential to influence understanding of any potential ecological impacts

DETERMINATION OF THE BEST METHODOLOGY FOR BATHYMETRY MAPPING USING SPOT 6 IMAGERY: A STUDY OF 12 EMPIRICAL ALGORITHMS

For the past four decades, many researchers have published a novel empirical methodology for bathymetry extraction using remote sensing data. However, a comparative analysis of each method has not yet been done. Which is important to determine the best method that gives a good accuracy prediction. This study focuses on empirical bathymetry extraction methodology for multispectral data with three visible band, specifically SPOT 6 Image. Twelve algorithms have been chosen intentionally, namely, 1) Ratio transform (RT); 2) Multiple linear regression (MLR); 3) Multiple nonlinear regression (RF); 4) Second-order polynomial of ratio transform (SPR); 5) Principle component (PC); 6) Multiple linear regression using relaxing uniformity assumption on water and atmosphere (KNW); 7) Semiparametric regression using depth-independent variables (SMP); 8) Semiparametric regression using spatial coordinates (STR); 9) Semiparametric regression using depth-independent variables and spatial coordinates (TNP), 10) bagging fitting ensemble (BAG); 11) least squares boosting fitting ensemble (LSB); and 12) support vector regression (SVR). This study assesses the performance of 12 empirical models for bathymetry calculations in two different areas: Gili Mantra Islands, West Nusa Tenggara and Menjangan Island, Bali. The estimated depth from each method was compared with echosounder data; RF, STR, and TNP results demonstrate higher accuracy ranges from 0.02 to 0.63 m more than other nine methods. The TNP algorithm, producing the most accurate results (Gili Mantra Island RMSE = 1.01 m and R2=0.82, Menjangan Island RMSE = 1.09 m and R2=0.45), proved to be the preferred algorithm for bathymetry mapping

Assessment of different models for bathymetry calculation using SPOT multispectral images in a high-turbidity area: the mouth of the Guadiana Estuary

Periodic calculation of coastal bathymetries can show the evolution of geomorpholo- gical features in active areas such as mesotidal estuary mouths. Bathymetries in shallow coastal areas have been addressed mainly by two technologies, lidar and optical remote sensing. Lidar provides good accuracy, but is an expensive technique, requiring planned flights for each region and dates of interest. Optical remote sensing acquires images periodically but its results are limited by water turbidity. Here we use a lidar bathymetry to compare different bathymetry computation methods using a SPOT optical image from a nearby date. Three statistical models (green-band, PCA correlations, and GLM) were applied to obtain mathematical expressions to estimate bathymetry from that image: all gave errors lower than 1 m in an area with depths ranging from 0 to 6 m. These algorithms were then applied to images from three different dates, correcting the effects caused by different tidal and atmospheric condi- tions. We show how this allows the study of morphological changes. We discuss the accuracy obtained with respect to the reference bathymetry (0.9 m on average, but less than 0.5 m in low-turbidity areas), the effects of the turbidity on our estimations, and compare both with previously published results. The results show that this approach is effective and allows identification of known features of coastal dynamics, and thus it would be an important step towards short-term bathymetry monitoring based on optical satellite remote sensing.Ministerio de Ciencia e Innovación CSO2010-15807Consejería de Innovación, Ciencia y Empresa P10-RNM-620

Physics-based satellite-derived bathymetry for nearshore coastal waters in North America

Accurate bathymetric information is fundamental to safe maritime navigation and infrastructure development in the coastal zone, but is expensive to acquire with traditional methods. Satellite-derived bathymetry (SDB) has the potential to produce bathymetric maps at dramatically reduced cost per unit area and physics-based radiative transfer model inversion methods have been developed for this purpose. This thesis demonstrates the potential of physics-based SDB in North American coastal waters. First the utility of Landsat-8 data for SDB in Canadian waters was demonstrated. Given the need for precise atmospheric correction (AC) for deriving robust ocean color products such as bathymetry, the performances of different AC algorithms were then evaluated to determine the most appropriate AC algorithm for deriving ocean colour products such as bathymetry. Subsequently, an approach to minimize AC error was demonstrated for SDB in a coastal environment in Florida Keys, USA. Finally, an ensemble approach based on multiple images, with acquisitions ranging from optimal to sub-optimal conditions, was demonstrated. Based on the findings of this thesis, it was concluded that: (1) Landsat-8 data hold great promise for physics-based SDB in coastal environments, (2) the problem posed by imprecise AC can be minimized by assessing and quantifying bias as a function of environmental factors, and then removing that bias in the atmospherically corrected images, from which bathymetry is estimated, and (3) an ensemble approach to SDB can produce results that are very similar to those obtained with the best individual image, but can be used to reduce time spent on pre-screening and filtering of scenes

Bathymetry of Alaskan arctic lakes: a key to resource inventory with remote-sensing methods

Thesis (Ph.D.) University of Alaska Fairbanks, 1982Water depth is a major factor in predicting resources associated with tens-of-thousands of uninventoried Alaskan arctic lakes. Lakes were studied for physical, chemical, and biological resources related to water depth in 3 specific areas along a north/south transect extending from Pt. Barrow on the Arctic Ocean to the foothills of the Brooks Range. Side-Looking Airborne Radar (SLAR) imagery was acquired over the same study transect to investigate its application for determining lake depth. Ice thicknesses, necessary for the interpretation of depth contours from SLAR imagery, were measured along with other parameters in the study lakes throughout the winter 1978-79. This ice-thickness data and sequential SLAR images are used to illustrate a method of contouring water depths in arctic lakes. This is based on changes in intensity of SLAR signal return which define the zone at which ice cover contacts the bottom. This intensity is a function of physical and dielectric properties of the snow, ice, water, bottom substrates, and ice inclusions within these lakes. A computer program was developed to manipulate Landsat satellite digital data and compile a master file of lakes and their computer-calculated surface features (i.e. area, perimeter, crenulation, and centroid). The master file uniquely identifies each computer catalogued lake by latitude and longitude and stores the calculated features in a data base that can be retrieved for a specified geographic ABSTRACT area. Each lake record also provides storage space for resource data collected outside the computer generated data. The application of these remote-sensing tools and the knowledge of aquatic resources associated with bathymetry add to our ability for regional inventory, classification, and management of arctic lake resources

Satellite Water Column Data for Hydrography

Optical-band satellite images selected for satellite-derived bathymetry (SDB) analysis require clear water with low turbidity. As a result, image selection processes exclude images with excess turbidity regardless of cause. Images with water-column turbidity contain valuable information. Under certain conditions, vortex patterns in navigable waters are present in satellite imagery. Although vortex-induced turbidity excludes these images from SDB processing, the presence and shape of these vortices contain information relevant to hydrography. In this observational study, we use two case studies to describe vortex patterns and environmental conditions leading to their formation and then explore novel hydrographic survey applications of these phenomena.Las imágenes satelitales de banda óptica seleccionadas para el análisis debatimetría derivada de satélites (SDB) requieren agua clara con una baja turbidez.Como resultado, los procesos de selección de imágenes excluyen las imágenescon exceso de turbidez, independientemente de la causa.Las imágenes con turbidez en la columna de agua contienen información valiosa.En determinadas condiciones, los patrones de vórtices en aguas navegables estánpresentes en las imágenes satelitales. Aunque la turbidez inducida por losvórtices excluye estas imágenes del procesado SDB, la presencia y la forma deestos vórtices contienen información relevante para la hidrografía. En este estudiode observación, utilizamos dos estudios de casos para describir los patrones delos vórtices y las condiciones ambientales que llevan a su formación y luegoexploramos nuevas aplicaciones de estos fenómenos a los levantamientoshidrográficos.Les images satellitaires en bande optique sélectionnées pour l'analyse de labathymétrie dérivée par satellite (SDB) nécessitent une eau claire et de faibleturbidité. Par conséquent, les processus de sélection d'images excluent les imagesprésentant une turbidité excessive, quelle qu'en soit la cause.Les images qui montrent la turbidité dans la colonne d'eau contiennent desinformations précieuses. Dans certaines conditions, les images satellitairesmontrent des tourbillons dans les eaux navigables. Bien que la turbidité induite parles tourbillons exclue ces images du traitement SDB, la présence et la forme deces tourbillons contiennent des informations pertinentes pour l'hydrographie. Danscette étude basée sur l'observation, nous utilisons deux études de cas pour décrireles configurations des tourbillons et les conditions environnementales qui ontconduit à leur formation, puis nous explorons de nouvelles applications de cesphénomènes pour les levés hydrographiques